Monetary Policy in Emerging Markets: Taming the Cycle; by ... - IMF

WP/13/96

Monetary Policy in Emerging Markets: Taming the Cycle Donal McGettigan, Kenji Moriyama, J. Noah Ndela Ntsama, Francois Painchaud, Haonan Qu, and Chad Steinberg

© 2013 International Monetary Fund

WP/13/96

IMF Working Paper Strategy, Policy and Review Department Monetary Policy in Emerging Markets: Taming the Cycle1 Prepared by Donal McGettigan, Kenji Moriyama, J. Noah Ndela Ntsama, Francois Painchaud, Haonan Qu, and Chad Steinberg Authorized for distribution by James Roaf May 2013 Abstract This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate. In contrast to advanced markets (AMs), procyclical monetary policy has been a problem for emerging markets (EMs), with macroeconomic policies amplifying economic upswings and deepening downturns. The stark difference in policy has not been subject to extensive study and this paper attempts to address the gap. Key findings, using a large sample of EMs over the past 50 years, are: (i) EMs have adopted increasingly countercyclical monetary policy over time, although large differences remain among EMs and policies became more procyclical during the recent crisis. (ii) Inflation targeting and better institutions have been key factors behind the move to countercyclicality. (iii) Only deep financial markets allow EMs with flexible exchange rate regimes turn countercyclical. (iv) More countercyclical policy is associated with far less volatile output. The economically meaningful impact of IT on monetary policy countercyclicality and output variability is another reason in its favor, over and above better inflation outcomes.

JEL Classification Numbers: E52, F41 Keywords: Monetary Policy, Countercyclical Policy, Emerging Markets Authors’ E-Mail Address:[email protected]; [email protected] 1

This paper benefited from excellent research assistance from Trung Bui, Yuan Guo and Malika Pant. It also benefited from helpful comments from Lorenzo Giorgianni, Ioannis Halikias, and James Roaf and from other colleagues in Strategy, Policy, and Review Department, other Departments at the IMF, and Executive Directors. The usual disclaimer applies.

2

Contents

Page

I. Introduction ............................................................................................................................3 II. Literature Review ..................................................................................................................3 III. Analysis of Monetary Policy Cyclicality .............................................................................4 IV. Determinants of Cyclicality .................................................................................................9 V. Cyclicality of Monetary Policy and Output Variability ......................................................12 VI. Case Study—The Case of Chile ........................................................................................13 VII. Conclusions and Policy Recommendations .....................................................................16 TABLES 1. Explaining CoMP in EMs ....................................................................................................11 2. Result of Regression on Log Output Volatility ...................................................................13 3. Result of Regression on Cyclicality of Monetary Policy in Chile .......................................16 4. Country Date Coverage of CoMP ........................................................................................19 5. Taylor Rule Results: Entire Sample Period .........................................................................20 6. Explaining CoMP in AMs ...................................................................................................21 7. Cross Country Regressions for EMs in 1995 and 2007 .......................................................21 BOX Estimates of Taylor Coefficients in Literature.........................................................................18 APPENDIXES I. Additional Tables and Figures..............................................................................................19 II. Data and Sources .................................................................................................................25 References ................................................................................................................................27

3 I.

INTRODUCTION

Procyclical policy has been a problem for emerging markets (EMs), with macroeconomic policies amplifying economic upswings and deepening downturns.2 This contrasts sharply with advanced markets (AMs), where policies tend to be countercyclical. Much attention has been given to the cyclical nature of fiscal policy in EMs. The literature provides ample evidence that fiscal policy in EMs has been procyclical, but with recent work finding it has become less so due to stronger institutions.3 By contrast, the literature on monetary policy cyclicality in EMs is sparse.4 It mostly contrasts the countercyclical nature of monetary policy in AMs and the procyclical stance of EMs. It also provides tentative evidence of a recent shift towards more countercyclical policy (“graduation”) in EMs, in parallel with improvements in the cyclical nature of EM fiscal policy. The literature also touches briefly on possible causes of such graduation. This paper addresses this gap and finds that many EMs have shifted to countercyclical monetary policy, with inflation targeting (IT) and strengthened institutions as key causal factors. This suggests additional policy benefits from moving to IT, and all that it involves, over and beyond its contribution to lower inflation in EMs. The rest of the paper is as follows. Section II reviews the literature on EM monetary policy cyclicality. Section III measures EM and AM monetary policy cyclicality across time for a wide variety of countries. Section IV examines possible causes. Section V assesses the implications of cyclicality for output variability. Section VI presents a case study of Chile, an EM that has strengthened institutions and adopted IT, allowing it to pursue more countercyclical monetary policy. Section VII concludes. Data and sources are discussed in Appendices I and II. II. LITERATURE REVIEW The key findings of the sparse literature of monetary policy cyclicality in EMs are: (i) while AMs are overwhelmingly countercyclical in their conduct of monetary policy, the same does not hold for EMs; and (ii) monetary policy in EMs is becoming more countercyclical, reflecting better underlying macroeconomic conditions and institutional improvements. The main relevant studies are:

2

See, for example, Kaminsky, Reinhart and Vegh (2005).

3

See, for example, Gavin and Perotti (1997), Lane (2003), Akitoby, Clements, Gupta, and Inchauste (2004), Kaminsky, Reinhart and Vegh (2004), Talvi and Vegh (2005), Alesina, Campante, and Tabellini (2008), Ilzetzki and Vegh (2008), and Frankel, Vegh, and Vuletin (2012).

4

The few studies that exist include Kaminsky, Reinhart and Vegh (2005), Coulibaly (2012), Takáts (2012), and Vegh and Vuletin (2012).

4 

Kaminsky, Reinhart and Vegh (2005) present the first systematic effort to document empirically the cyclical properties of monetary policy in EMs. Using data for 104 countries over 1960-2003, they find that most OECD countries have countercyclical monetary policy, while EMs are mostly procyclical or acyclical.



Coulibaly (2012) focuses on EM policy rates and credit growth during the recent crisis. He finds evidence of “graduation” to countercyclical monetary policy and ascribes this to factors such as macroeconomic fundamentals, vulnerabilities, financial sector reform, and adoption of IT (with more countercyclicality noted in EMs as these factors improved).



Vegh and Vuletin (2012) find evidence of EM “graduation.” They find that more than a third of EMs graduated in the 2000s, on top of the third that already had such policies in place. (Only 7 percent reverted to procyclical monetary policy.) They regard the lack of exchange rate flexibility, in turn related to institutional quality, as a key determining factor of procyclicality.

But there are several gaps in the literature. To date, this emerging literature primarily examines the relationship between nominal rates and real output, which could be problematic, especially for EMs with large swings in inflation. Moreover, analysis to date is not focused on the underlying reasons behind these differences in performance over time and across countries, which is critical for policy prescriptions. The aim of this paper is to help address these gaps. III.

ANALYSIS OF MONETARY POLICY CYCLICALITY

This section documents systematically a major shift in the cyclical behavior of monetary policy over the last half century across a wide sample of AMs and EMs. The cyclicality of monetary policy is measured by the 10-year backward correlation between the cyclical component of real GDP and the cyclical component of the real short-term interest rate, where the latter is taken as a proxy for the stance of monetary policy.5 6 A positive correlation is indicative of countercyclical monetary policy, while a negative correlation indicates procyclical monetary policy. We label this new measure the Cyclicality of Monetary Policy (CoMP). Our dataset covers 84 countries—35 AMs and 49 EMs—over 1960 to 2011.7

5

We use the central bank discount rate as our short-term interest rate due to its longer availability than other variables. Interest rates are deflated using current CPI inflation and are cyclically adjusted. The paper also cross checked against a key monetary aggregate (private credit) to detect counter-cyclicality. The main storyline does not change from that based on the real central bank discount rate. 6

The cyclical component is derived from the average of the estimated trend using a HP filter with lambda 100 and 6.25. In order to avoid the usual end-point distortions associated with the HP filter, each data series beyond 2017 is extended using the 2017 growth rate.

7

See Table 4 in Appendix I for details, including on data coverage for individual countries.

5 The analysis confirms that monetary policy in AMs is typically more countercyclical than in EMs, but that both AMs and EMs have become more countercyclical. Figure 14 in Appendix I shows the computed correlation between the cyclical component of GDP and the cyclical component of the real short-term interest rate. A positive correlation is indicative of countercyclical monetary policy, while a negative correlation indicates procyclical monetary policy. The figure is divided into three periods: (i) 1960-2007, the full period (i) 1960-1995, the early period, and (iii) 1996-2007, the latter period. Our analysis, in general, concentrates on the period before 2007 to help abstract from exceptional factors that affected monetary policy most recently (see below). The charts show that AMs are more typically countercyclical in their application of monetary policy than EMs (top panel) and that AMs have become almost uniformly countercyclical since the late 1990s (bottom panel). EMs also improved, although the improvement is less striking. Still, large improvements were seen in, key EMs, including Colombia, Mexico, Malaysia, and the Philippines.8 Using nominal, rather than real, interest rates, shows a greater move to countercyclicality, especially for EMs (Figure 15 in Appendix I). Past studies of monetary policy cyclicality have used nominal, rather than real, rates. While a similar pattern emerges for AMs as in the real interest rate figure, EMs show an even stronger move towards countercyclical monetary policy using nominal rates. Despite these more promising EM results using nominal rates, for the remainder of the paper we focus on CoMP measures using real rates. This is because there appear more grounds for relating real interest rates to the real output gap—two real variables—rather than linking a nominal variable with a real output gap.9

8

9

Figure 1. Transitions 1.0 0.8

LBN CHE

More countercyclical during 1996-2007

0.6 0.4

Correlations during 1996-2007

Focusing on CoMP transitions, it is clear that EMs have adopted increasingly countercyclical monetary policy over time. This is apparent in Figure 1, which shows the cyclicality of monetary policy over 1960-1995 on the horizontal axis, and over 1996-2007 on the vertical axis. This figure divides covered countries into four “quadrant” categories along the lines of Vegh and Vuletin (2012), as explained by the chart’s four black sub-labels. The countries in the top-right quadrant are countries that have been countercyclical over the past fifty years, and not surprisingly, include many AMs. Over 1960–95, 68 percent of AMs (in red) were implementing counter-cyclical monetary

0.2

FRA AUT ISL DNK BEL ESP ITA ISR DEU FIN NZL MEX MYS KOR PHL COL SWE TWN IDNCYP EGY

EST

From Procyclical to Countercyclical

ECU CAN USA

LKA THANOR VEN IRL PRT PAK

SGP

0.0

CRI

GRC HUN

Procyclical in both periods

-0.6

TUR

IND JPN

URY MARDZA

GBR

Countercyclical in both periods NED JOR

TUN

PER

-0.2 -0.4

AUS ZAF

LUX

From Countercyclical to Procyclical

ARG BRA

-0.8 More procyclical during 1996-2007

-1.0 -1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

Correlations during 1960-1995 EMs

AMs

Source: IMF staff calculations

The findings may be less relevant for those countries that have no monetary independence.

That said, the countercyclicality of monetary policy may be understated using real rates if demand-led inflation shocks predominate, reducing measured real rates as output rises.

0.8

1.0

6 policy (countries situated on the right side of the figure) compared to 50 percent for EMs (in blue). Over 1996-2007, AMs have become almost uniformly countercyclical and more EMs (60 percent) were implementing counter-cyclical monetary policy (countries situated in the top part of the figure).10 11 The countries in the bottom-left quadrant are countries that have always been procyclical, and include mostly EMs. 12

In the shift toward more countercyclical policy, central banks transitioned through distinct periods. Figure 3 shows the simple average of our CoMP measure for all countries between 1960 and 2011.13 It illustrates that across the spectrum, central banks have indeed become more

Figure 2. EM Transitions (Average of Rolling Correlations During Each Period) 1.0 0.8 POL 1998

COL 1999

0.6 MYS

LBN

Average during 1996-2007

Inflation-targeting EMs appear to have been most successful in implementing countercyclical monetary policy. Figure 2 shows a comparison of correlations over both periods. The earlier period is replaced by a shorter time series reflecting data availability for EMs. As in the earlier chart, observations above the forty-five degree line indicate an improvement in policymaking, with those furthest away from the line showing the greatest improvement. Yellow identifies countries that adopted some version of IT and the label refers to the year the regime was adopted. By and large, a greater proportion of inflation targeters moved to countercyclical monetary policy than non-IT regimes. Notable improvements were made, for 0.6 example, by Chile, Indonesia, the 0.5 Philippines, and Poland. 0.4

0.4 BGR

IDN 2005

VEN PER 2002

CHL 1999 TUR 2006

EGY

0.0

MAR

-0.2

HUN 2001

MEX 2001

-0.4

ARG UKR

-0.6

MKD

THA 2000 DZA

BLR

CHN

HRV TUN JOR ALB LKA

PAK

PHL 2002

0.2

ZAF 2000

ECU

CRI

IND BRA 1999 JAM

URY

LVA KAZ

-0.8 -1.0 -1.0

-0.5

0.0

0.5

1.0

Average during 1993-1995 Source: IMF staf f calculations

Figure 3. CoMP over Time

Start of Great Moderation

Break Down of Bretton Woods System

Global Financial Crisis

0.3 0.2 0.1 0.0 -0.1 -0.2 1960

1965

1970

1975

1980

Great Moderation

1985

1990

All countries

1995 AMs

2000

2005

2010

EMs

Source: IMF staff calculations

10

The two periods are chosen based on Taylor rule break points. See below for details.

11

Results are robust to break point changes.

12

These results are also broadly consistent with the results presented in Vuletin and Vegh (2012) (Figure16 in Appendix)--- Vuletin and Vegh’s analysis, however, uses nominal rather than real interest rates, which shows an even sharper improvement for both advanced and emerging market economies over time. Nominal rates may not capture as accurately the stance of monetary policy, in particular in emerging markets where inflation is often high and volatile. 13

As noted before, our country-specific measure of monetary policy cyclicality is based on the 10-year backward correlation between the cyclical component of real GDP and the cyclical component of the real shortterm interest rate. Therefore, the average presented for 1980, is the country average of the correlations for each country over the previous ten years (1971 to 1980).

7 countercyclical in their monetary policy. We identify two noticeable periods of change. First, with the breakdown of the gold standard and the Bretton Woods system in the early 1970s, AMs steadily moved from acyclical/procyclical to countercyclical monetary policymaking. This likely illustrates the importance of more flexible exchange rate regimes in helping to achieve greater monetary policy independence. Second, during the period of the Great Moderation14 starting in 1984, countercyclicality improved for both advanced and emerging market economies, with the move especially striking for AMs. We will explore possible explanatory factors in more detail in the following section. Following the advent of the global crisis, monetary policy has also become decidedly less countercyclical across the board according to our CoMP measure. For AMs this in part likely reflects central banks running into the interest rate lower bound, and their inability to generate persistent negative real interest rates. Instead, many AMs shifted policy implementation from short-term interest rates to quantity-based policies and a heavier reliance on forward guidance. For EMs, global food and commodity price shock may have played a role given their large weight in many EM’s CPI baskets. Coming into the crisis, EM central banks were concerned with second round effects from the run-up in commodity prices, meaning that a full response to headline commodity-related inflation increases was not needed. After the crisis hit, inflation fell quickly with commodity prices, but capital also started to quickly flow back to the core. As a result, there was less room for EM central banks to loosen monetary policy, and less need from a strictly inflation viewpoint, increasing measured monetary policy procyclicality. Although there was an overall increase in countercyclicality prior to the crisis, large variations among EMs remain (Figure 4).15 From the start of the Great Moderation until the onset of the global financial crisis, AMs showed a clear shift towards countercyclical monetary policy, with the width of the distribution also narrowing as “laggers” caught up to “leaders” in monetary policy implementation. This is largely consistent with our earlier findings. In contrast, while EMs also improved, the advances have not been uniform. A Figure 4. CoMP Distribution for AMs and EMs AMs 45

EMs 35

1984 Median of 1984 2007 Median of 2007

40 35

1995 Median of 1995 2006 Median of 2006

30 25

30 25

20

20

15

15

10

10

5

5 0

0 -1.5

-1

-0.5

0

0.5

1

1.5

-1.5

-1

-0.5

0

0.5

1

1.5

Source: IMF staf f calculations

14

15

This refers to the period of decreased macroeconomic volatility explained in advanced economies.

Part of the reason for the more procyclical behavior in the earlier period for EMs may reflect procyclical disinflation from high levels of inflation.

8 comparison of the distributions between 1995 and 2006 16 show that while the number of EMs implementing countercyclical policy has increased, so has the number of procyclical EMs partly reflecting the arrival of transition countries with procyclical monetary policy. The resulting distribution shows a bimodal relationship where there are two group of emerging market economies: the countercyclicalists (on the right) and the procyclicalists (on the left).

The Taylor rule estimates also provide evidence of a change in monetary policy cyclicality around 1996-97 (Figure 6). We run Chow tests on country-specific Taylor rules to check for a break in the coefficient on the output gap. Figure 6 shows that the mode of the distribution of break points for EMs is in the 1996-97 period. This is also consistent with the presentation of the data in previous figures. Panel regressions are also supportive of this hypothesis.18

16

Figure 5. Correlations and Estimated Response to Output Gaps in Taylor Rule (All Sample Period, Unadjusted Real Interest Correlations) 4 ZAF

3 Responses to output gaps in Taylor Rule

We check these results by running a multitude of robustness checks. Our main strategy is to use the structure of Taylor rules to estimate Taylor coefficients on each country.17 Several variants of the Taylor rule are estimated with the full set of results presented in Table 5 in Appendix I. Figure 5 shows a strong and significant relationship between our simple correlation measures and the estimated coefficients from the basic Taylor rules (i.e., that on the output gap) that supports our use of the simple correlations. Interestingly, this relationship is strongest for IT regimes in EMs (yellow dots) and both IT (red) and non-IT (white) AMs. This “better fit” in part reflects a smaller bias in estimated Taylor coefficients for countries with less volatile output gaps.

y = 1.8943x + 0.4726 R² = 0.297

NED AUS ROM

2

1

0 KAZ

-1

-2 -0.8

UKR

-0.6

DEN COL DOM NORECU GBR FRA CAN PER BEL ITA POL JPN CRI SWE LKA ISL PRTUSA THA PAK GRC DEU LUX ISR NZL TUN SLV KOR FIN HRV PHL GTM VENAUT IDN LBN EST MYS HGK CHE LTU EGY SVK SRB CHL ESP BIH CYP SGP HUN JOR TWNIRL CZE ALB MLT ARM MKD LVA MAR BLR TUR IND CHNSVN DZAVNM ARG GEO URY MEX BGR RUS PAN JAM BRA

-0.4

-0.2

0.0

0.2

0.4

0.6

CoMP Source: IMF staf f calculations

Figure 6. Density of Structural Break Year by Chow Test 0.45 0.40 0.35 0.30 0.25

AMs EMs Overall

0.20 0.15 0.10 0.05 0.00 -0.05


The different time period reflects the different transition period for EMs and data availability.

17

The Taylor coefficient is defined as the coefficient on the output gap in the Taylor rule formulation in this paper (see Table 5 in Appendix I).

18

This is tested by inserting a break dummy for 1996 in a fixed-effect panel regression with CoMP as the dependent variable.

0.8

9 Figure 7. Comparison of Our CoMP Measures and Correlation Between Private Credit and Output Gap 1960-2009 Corelation between private credit and output gap

Another robustness check is conducted using monetary aggregates, as some EM central banks conduct monetary policy using other instruments. Our findings are broadly consistent with our interest-rate based findings. In particular, our CoMP measure is very strongly correlated to the correlation between monetary aggregate (private credit) and output gaps over the entire sample period, implying that CoMP is a good proxy for monetary policy stance even if the stance is characterized by monetary aggregates (see Figure 7).

1

45°

0.8

-1

-0.8

-0.6

CHN EMU DEU LUX CHE NED COL 0.6 MLT AUT SLV HGK KAZ POL SGP AUS GBR ISL ZAF CHL VNM LVAFIN 0.4 LTU BEL CAN TUN THA NZL MYS RUS CZE JPN ISR UKR IRL NOR USA LBN SWE ITA PAK PRT FRA 0.2 MKD ARM TWN KOR PHL ESP VEN JOR SVN GRC LKA ECU CYP DEN MAR 0 SVK EST BLR 0.2 PER -0.4 -0.2 EGY 0BGR 0.4 0.6 0.8 1 IDN GEOBRA -0.2 HRV IND DZA CRI HUN TUR URY ROM -0.4

MEX DOM

ARG ALB

-0.6 -0.8 -1 CoMP


Our broad findings thus far are as follows: 

EMs have adopted more countercyclical monetary policy over time (at least prior to the recent crisis) and have emulated AMs in this respect;



Adoption of IT appears an important supporting factor;



Yet many EMs continue to pursue procyclical monetary policies, which could have serious economic costs. IV.

DETERMINANTS OF CYCLICALITY

The second part of the analysis attempts to explain both the differences across EMs and over time in the degree of monetary policy cyclicality. The policy variable of interest is our measure of monetary policy cyclicality discussed earlier (CoMP). A number of policy instruments are explored as possible explanatory variables, including the monetary policy regime, the exchange rate regime, financial market development, and institutional strength. The strength of this analysis is bolstered by the large number of countries examined and the extensive period of time covered. As far as we know, this is the first study to systematically examine the determinants of monetary policy countercyclicality in EMs in such a comprehensive manner. To conduct the analysis, we build a cross-country data set covering 64 countries (23 AMs and 41 EMs) between 1985 and 2011.19 The data set includes variables on both policy regimes and country economic characteristics. The data set is unbalanced with AMs generally covered for longer time periods than EMs. Our main data sources are set out in Appendix II. 19

The variables are aligned with CoMP by taking averages over the same 10-year period. Since ICRG data are available only after 1985 and thus its rolling correlations are available only after 1995, the sample period is extended to 2011 in order to increase sample size. Moreover, as these are rolling correlations over the previous ten years, developments since 2008 do not excessively affect the last three years in the sample.

10

Our priors are as follows: (i)

We expect the inflation targeting dummy to enter the equation with a positive sign, meaning that it is expected to help monetary policy become more countercyclical. A priori, IT regimes are expected to have strong monetary institutions, be more independent, and are generally thought to have improved monetary policy making within the standard business cycle, including through better communications and the anchoring of inflation expectations.

(ii)

We expect the institutional variable to also enter the equation with a positive sign.20 Stronger institutions are generally associated with stronger policies.

(iii)

The exchange rate regime variable—which takes on a smaller value when the regime is more rigid—is also expected to be positive. In fixed regimes with open capital accounts, capital flows can complicate the conduct of monetary policy, with monetary policy being loosened in periods of strong capital inflows and growth, and being tightened in the event of outflows. But “fear of floating” may run counter to this effect in EMs.

(iv)

The financial reform index is expected to be positive. Deeper and more liberal financial markets help strengthen the monetary policy transmission mechanism of movements in policy rates. Thus, it should be easier for central banks to conduct countercyclical policy in environments where financial markets are deep, and as a consequence the transmission mechanism is well established.

We find that both inflation targeting and institutions are significant and robust drivers of monetary policy countercyclicality. (Regressions estimated with fixed effects for EMs countries are presented in Table 1.21) These results withstand a multitude of specification and robustness checks, with both variables remaining significant and largely unchanged in the multivariate specifications. The signs of the variables are also consistent with our priors. Namely, countries that have implemented IT regimes and/or have improved their institutions tend to have more countercyclical monetary policy. As these results are based on withincountry variation regressions, we also test for robustness by running a parallel cross-country regressions (see Table 7 in Appendix I), which confirms the importance of both institutions and IT regimes for the conduct of countercyclical monetary policy.

20

While central bank independence index is another possible candidate to be used as a proxy for institutional strength, the paper does not use it due to data availability constraints. 21 Similar regressions for AM countries are presented in Table 6 in Appendix I.

11 Table 1. Explaining CoMP in EMs Dependent Variables IT dummy

(1) CoMP

(2) CoMP

(3) CoMP

(4) CoMP

0.571 *** (0.171)

FX regime

(5) CoMP

(6) CoMP

0.598 *** (0.175) -0.204 (0.283)

Institution (Government stability in ICRG)

-1.535 ** (0.733) 0.085 (0.054)

0.104 ** (0.049)

Financial deepening (Financial reform index)

-0.294 (0.643)

Adjusted R2 Model

0.091 * (0.055) -1.359 (1.085)

FX regime*financial deepening Number of samples

0.760 *** (0.209)

1.344 (1.029) 710

700

663

0.117

0.046

0.052

FE

FE

FE

663

601

0.138

0.166

FE

FE

623 0.037 FE

Number in parentheses indicate standard errors. *** p